'
GarageType', 'BsmtCond', 'BsmtExposure', 'BsmtQual', 'BsmtFinType2', 'BsmtFinType1', 'MasVnrType', 'MasVnrArea', 'MSZoning', 'BsmtH
alfBath', 'Utilities', 'Functional', 'BsmtFullBath', 'BsmtFinSF1', 'Exterior1st', 'Exterior2nd', 'BsmtFinSF2', 'BsmtUnfSF', 'TotalBs
mtSF', 'SaleType', 'Electrical', 'KitchenQual', 'GarageArea', 'GarageCars']
In [25]:
missing_col = backup['index'].tolist()
for i in range(len(missing_col)):
if missing_col[i] in cat_cols:
memo_cat.append(missing_col[i])
elif missing_col[i] in num_cols:
memo_num.append(missing_col[i])
print(memo_cat)
print(memo_num)
[
'PoolQC', 'MiscFeature', 'Alley', 'Fence', 'FireplaceQu', 'GarageCond', 'GarageQual', 'GarageFinish', 'GarageType', 'BsmtCond', 'Bs
mtExposure', 'BsmtQual', 'BsmtFinType2', 'BsmtFinType1', 'MasVnrType', 'MSZoning', 'Utilities', 'Functional', 'Exterior1st', 'Exteri
or2nd', 'SaleType', 'Electrical', 'KitchenQual']
[
'
'LotFrontage', 'GarageYrBlt', 'MasVnrArea', 'BsmtHalfBath', 'BsmtFullBath', 'BsmtFinSF1', 'BsmtFinSF2', 'BsmtUnfSF', 'TotalBsmtSF',
GarageArea', 'GarageCars']
missing categorical columns: ['PoolQC', 'MiscFeature', 'Alley', 'Fence', 'FireplaceQu', 'GarageCond', 'GarageQual', 'GarageFinish', 'GarageType',
'
'
BsmtCond', 'BsmtExposure', 'BsmtQual', 'BsmtFinType2', 'BsmtFinType1', 'MasVnrType', 'MSZoning', 'Utilities', 'Functional', 'Exterior1st', 'Exterior2nd',
SaleType', 'Electrical', 'KitchenQual']
missing numerical columns: ['LotFrontage', 'GarageYrBlt', 'MasVnrArea', 'BsmtHalfBath', 'BsmtFullBath', 'BsmtFinSF1', 'BsmtFinSF2', 'BsmtUnfSF',
'TotalBsmtSF', 'GarageArea', 'GarageCars']
In [26]:
mean_GarageYrBlt = all_data['GarageYrBlt'].mean()
np.floor(mean_GarageYrBlt)
1
978.0
Out[26]:
In [27]:
cols2 = ["MSZoning", "BsmtFullBath", "BsmtHalfBath", "Utilities", "SaleType","Exterior1st", "Exterior2nd"]
for col in cols2:
all_data[col] = all_data[col].fillna(all_data[col].mode()[0])